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Since 1986 - Covering the Fastest Computers in the World and the People Who Run ThemSun, 02 Aug 2015 12:39:43 +0000en-UShourly1http://wordpress.org/?v=4.2.3Michio Kaku Sketches Technological Wonderland of the Future at SC12http://www.hpcwire.com/2012/11/16/michio_kaku_sketches_technological_wonderland_of_the_future_at_sc12/?utm_source=rss&utm_medium=rss&utm_campaign=michio_kaku_sketches_technological_wonderland_of_the_future_at_sc12
http://www.hpcwire.com/2012/11/16/michio_kaku_sketches_technological_wonderland_of_the_future_at_sc12/#commentsFri, 16 Nov 2012 08:00:00 +0000http://www.hpcwire.com/?p=4279<img style="float: left;" src="http://media2.hpcwire.com/hpcwire/Michio_Kaku_small.jpg" alt="" width="100" height="95" />Imagine a world where a computer chip costs just a penny. They could be embedded anywhere and everywhere. Celebrity physicist Michio Kaku talked about the implications of this and much more in his much-anticipated keynote address at Supercomputing 2012 (SC12) this week in Salt Lake City, where he discussed the huge role that high performance computing will play in the year 2100.

]]>Imagine a world where a computer chip costs just a penny. They could be embedded anywhere and everywhere, including the wallpaper of your house. Instead of sitting home alone on a Friday night drinking oneself into a stupor, one could simply go to his wall and look up others who are alone looking at their wall on a Friday night in order to find a companion for the night.

Dr. Michio Kaku, celebrity physicist who has written New York Times Bestselling books, Physics of the Impossible and Physics of the Future, talked about the implications of this smart wall and much more in his much-anticipated keynote address at Supercomputing 2012 (SC12) this week in Salt Lake City, where he discussed the huge role that high performance computing will play in the year 2100.

Since the 18th century, science and technology have been key to attaining wealth in this world, Kaku observed. When physicists figured out the laws of thermodynamics and were thus able to calculate the amount of energy and power one could derive from manipulating steam, the Industrial Revolution ensued. The steel mills and railroads that followed generated tremendous revenue, but after too much of that wealth was invested in railroads on the London Stock Exchange, the system ground to a halt in 1850.

Incidentally, in 1850 the Industrial Revolution was just getting underway in the United States. While part of that had to do with the relative youth of the country, an amusing part (in a historical sense anyway) had to do with Britain’s flat refusal to let so much as a blueprint leave their country. It wasn’t until Francis Cabot Lowell returned to America with the technical specifications in his photographic memory that the revolution took off in the US.

Either way, by the time Maxwell’s light equations and Faraday’s force field lines began paving the way for physicists harnessing the power of electricity and magnetism, the United States had clearly made up their deficit from the Industrial Revolution delay. But once again, an unsustainable portion of the ensuing wealth was poured into one thing, in this case the utilities. As a result, the New York Stock Exchange crash of 1929 plunged the US into the Great Depression, Kaku noted.

Physicists, as Kaku continued setting the historical scene, then further manipulated the laws of electricity and magnetism to create machines that could add large numbers together by simply flipping little magnets. These machines were called computers. The led to a third expansion of wealth, a third improper allocation of investments (this time in the housing market), and a third economic collapse.

This is an intriguing and relevant history for one paramount reason: the people in the audience listening to Dr. Kaku talk about the results of the first three technological revolutions will be the people responsible for the fourth. Kaku calls the upcoming 80 years an “era of high technology.” Some may call it the Information Revolution. Whatever the new era happens to be called, advances in supercomputing will drive it.

The benefits as Dr. Kaku predicts them are vast and can be best described in terms of vocabulary that will become obsolete. Cars will be able to drive themselves, essentially eliminating the 30,000 auto accident deaths a year in the United States. As Kaku puts it, the term “car accident” will become passé. In fifty years, the word “traffic” may refer more to the 1960’s musical group than a bottleneck of automobiles.

Like the word “polio,” the word “tumor” could be relegated to a reminder of unpleasant times past, as smart toilets equipped with computer chips hooked up to a supercomputing network analyze DNA for signs of cancerous cells. Destroying those cancerous cells individually through nanotechnology, instead of through brute force chemotherapy could become possible. Perhaps most impressively, MRIs could literally be conducted from a Star Trek-like Tricorder, as chips extend magnetic fields from supercomputers such that they envelop a person like a natural MRI machine.

Further, like society simply accepts running water and electricity as facts of life that need not be mentioned, computers are likely to be accepted a similar fact of life. As computer chips are imprinted onto almost everything, from walls to paper, to clothing, to contact lenses, the entire world becomes, in essence, one large, networked computer.How will this all happen? Through a system of mass producing computer chips where each chip costs about a penny. While Kaku leaves it somewhat unclear how exactly that will happen (he’s a string theory physicist after all), it is clear that the path is not through silicon. Moore’s Law, the physical constraint which allows chip size to halve every 18 months or so, is slowing down.

That notion led to possibly the most harrowing possibility Kaku brought up: Silicon Valley becoming somewhat of a rust belt in the next 20 to 25 years. However, this should not be news to those in the know. As with previous technological advancements, businesses will have to adapt or be left by the wayside.

Maybe carbon nanotubes will take silicon’s place. Maybe that job falls to quanta. Either way, according to Kaku, the cheapening of these computing resources will lead to a much more automated the needs of society.

Of course, with increased automation comes an anxiety that the automation will replace humans. To a certain extent they will, says Kaku, but not to the extent that many may fear. It is important to remember that computers at their core are highly intricate adding machines. So only those with jobs that are highly iterative and repetitive, accountants for example, may need to worry, he argues.

The marketplace as Kaku sees it is shifting from a commodity-based system to one based in intelligence and creativity. For example, computer hardware can be mass-produced without much human intervention. Software cannot. It requires common sense, intuition, and creativity to produce software. Jobs that require those skills will persist. For the most part, those jobs will require a fair amount of higher education. Those which don’t require common sense, intuition, and creativity—the most boring of desk jobs—will cease to exist according to Kaku.

An audience member brought up an interesting point during the Q and A session: if we know that this upcoming information revolution will come to a head in 80 years or so, how do we avoid the bubble bursting once again? According to Kaku, the answer lies in changing investment rules to control reckless speculation.

Interestingly, the nature of the oncoming information revolution might actually be able to prevent such unsustainable growth. Today’s predictive analytics are far superior to those of four years ago and may have been able to warn investors when markets become over-heated.

As SC12 wraps up, it is important to remember how key the HPC industry will be in advancing society throughout the next 80 years. Dr. Kaku was preaching to the choir here in his keynote speech, but those songs resonate with scientific and societal reality.

]]>Łukasz Kaiser, a computer scientist from Paris Diderot University, has created a method that trains systems to learn board games. After being fed two-minute video clips of humans playing classics like Pawns, Connect 4, Gomoku and Breakthrough, a computer was able to understand the rules and outcomes of each game. Yesterday, Wired published an article about the project and described the software behind it.

Machine learning of this caliber can bring to mind scary scenarios of computers run amok. In fact, the concept was used in the 1983 science-fiction film War Games, where a military computer confused reality with board games. In this case, the program used a much safer test machine, a single-core laptop with 4GB of memory.

In his paper, Kaiser pointed out a number of key differences between previous experiments and his own. He mentioned that applications from other game-learning studies based on visual recognition required significant background knowledge and only worked with specific games. In this case, the algorithm would need only a few demonstrations and minimal background knowledge.

To achieve more functionality with less data, the project decided to forego using a popular inductive learning program (ILP) called Progol. Kaiser found that while Progol is a successful ILP application, it was not well suited for understanding games in this context.

“To be able to learn games such as Connect4 or Gomoku from short demonstration videos and with minimal background knowledge, we go back and investigate the basic assumptions of inductive logic programming,” he said.

The new algorithm used relational structures that could recognize common game elements like rows and columns as well as play styles. It then used a general game-playing program to build different types of tactics. The paper concluded that the model could be easily ported for other problem solving applications.

“This combination allowed it to generate very short and intuitive formulas in the experiments we performed, and there is strong theoretical evidence that it will generalize to other problems,” Kaiser explained.

Eventually, he expects the new algorithm to assist in the creation of intelligent robots that can employ structured learning. While the concept may induce fears of robotic rebellions, the application seems far from dangerous. At this point, the program could probably be tripped up with something as simple as a game of Monopoly.

]]>In the second and final game of the Jeopardy match televised Wednesday night, Watson prevailed once again, beating Ken Jennings and Brad Rutter decisively. The two-game total ended with Watson at $77,147, Jennings at $24,000 and Rutter at $21,600.

In the first round of Wednesday’s game, Jennings and Rutter held their own, answering a good share of the clues correctly and beating Watson to the buzzer in some cases, even when IBM’s computer had computed the correct response. At the end of the round, Jennings was ahead with $8,600, with Watson in second place at 4,800, and Rutter bringing up the rear with $2,400.

In the Double Jeopardy round, Jennings continued his hot streak, at one point leading Watson $15,000 to $6,273. Unflustered, Watson slowly worked its way back to the top. The computer’s most impressive response was on this clue: ITCHY (THE MOUSE) & SCRATCHY (THE CAT) STARRED IN “SKINLESS IN SEATTLE” ON A SHOW WITHIN THIS FOX SHOW. “What is The Simpsons,” replied Watson. The answer wasn’t impressive in the sense that it was able to correlate an episode title with the name of the TV show — that would have been an easy lookup — but that it was able to filter out the less important details and discern that the clue was even asking for show’s name.

By the time the Double Jeopardy round was over, Watson had accumulated $23,440, with Jennings at $18,200 and Rutter at $5,600. The Final Jeopardy clue — WILLIAM WILKINSON’S “AN ACCOUNT OF THE PRINICIPALITIES OF WALLACHIA AND MODAVIA” INSPIRED THIS AUTHOR’S MOST FAMOUS NOVEL — was an obscure reference to19th century Dracula author Bram Stoker. It was answered correctly by all three contestants. Watson, realizing that Jennings could win the game by betting high, wagered $17,973, bringing the computer’s nightly total to $41,413.

As for Watson’s future, the machine will be leaving the gameshow circuit and will be applying its AI smarts to the healthcare arena. On Thursday, IBM announced it will team with speech recognition company Nuance Communications, as well as Columbia University Medical Center and the University of Maryland School of Medicine, to commercialize the technology for medical diagnoses. From the IBM press release:

For example, a doctor considering a patient’s diagnosis could use Watson’s analytics technology, in conjunction with Nuance’s voice and clinical language understanding solutions, to rapidly consider all the related texts, reference materials, prior cases, and latest knowledge in journals and medical literature to gain evidence from many more potential sources than previously possible. This could help medical professionals confidently determine the most likely diagnosis and treatment options.

]]>Wondering why your computer just crashed again? Its memory might be to blame, according to real-world Google research that finds error rates higher than what earlier work showed. With hundreds of thousands of computers in its data centers, Google can collect an abundance of real-world data about how those machines actually work. That’s exactly what the company did for a research paper that found error rates are surprisingly high.